Noise Reduction in Time-Gated Spectroscopy

ABSTRACT

Systems and methods for reducing fluorescence and systematic noise in time-gated spectroscopy are disclosed. Exemplary methods include: a method for reducing fluorescence and systematic noise in time-gated spectroscopy may comprise: providing first light using an excitation light source; receiving, by a detector, first scattered light from a material responsive to the first light during a first time window; detecting a peak intensity of the first scattered light; receiving, by the detector, second scattered light from the material responsive to the first light during a second time window; detecting a peak intensity of the second scattered light; recovering a spectrum of the material by taking a ratio of the peak intensity of the first scattered light and the peak intensity of the second scattered light; and identifying at least one molecule of the material using the recovered spectrum and a database of identified spectra.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present continuation application claims the priority benefit of U.S.Non-Provisional patent application Ser. No. 17/003,825 filed on Aug. 26,2020 and titled “Advanced Fluorescence and Systemic Noise Reduction inTime-Gated Spectroscopy,” which claims the priority benefit of U.S.Non-Provisional patent application Ser. No. 16/289,596 filed on Feb. 28,2019 and titled “Fluorescence and Systemic Noise Reduction in Time-GatedSpectroscopy,” all of which are hereby incorporated by reference intheir entireties.

TECHNICAL FIELD

The present technology relates generally to spectral imaging, and morespecifically to time-resolved spectroscopy.

BACKGROUND

The approaches described in this section could be pursued but are notnecessarily approaches that have previously been conceived or pursued.Therefore, unless otherwise indicated, it should not be assumed that anyof the approaches described in this section qualify as prior art merelyby virtue of their inclusion in this section.

Spectroscopy (or spectrography) refers to techniques that employradiation in order to obtain data on the structure and properties ofmatter. Spectroscopy involves measuring and interpreting spectra thatarise from the interaction of electromagnetic radiation (e.g., a form ofenergy propagated in the form of electromagnetic waves) with matter.Spectroscopy is concerned with the absorption, emission, or scatteringof electromagnetic radiation by atoms or molecules.

Spectroscopy can include shining a beam of electromagnetic radiationonto a desired sample in order to observe how it responds to suchstimulus. The response can be recorded as a function of radiationwavelength, and a plot of such responses can represent a spectrum. Theenergy of light (e.g., from low-energy radio waves to high-energygamma-rays) can result in producing a spectrum.

SUMMARY

This summary is provided to introduce a selection of concepts in asimplified form that are further described in the Detailed Descriptionbelow. This summary is not intended to identify key features oressential features of the claimed subject matter, nor is it intended tobe used as an aid in determining the scope of the claimed subjectmatter.

The present disclosure is related to various systems and methods forfluorescence and systemic noise reduction in time-gated spectroscopy.Specifically, a method for reducing fluorescence and systematic noise intime-gated spectroscopy may comprise: providing first light using anexcitation light source; receiving, by a detector, first scattered lightfrom a material responsive to the first light during a first time windowhaving a first duration, the first scattered light having substantialRaman signal, the first scattered light having a first wavelength;detecting a peak intensity of the first scattered light; receiving, bythe detector, second scattered light from the material responsive to thefirst light during a second time window having a second duration, thesecond scattered light having little Raman signal, the second scatteredlight having the first wavelength; detecting a peak intensity of thesecond scattered light; providing second light using the excitationlight source; receiving, by the detector, third scattered light from thematerial responsive to the second light during a third time windowhaving the first duration, the third scattered light having substantialRaman signal, the third scattered light having a second wavelength;detecting a peak intensity of the third scattered light; receiving, bythe detector, fourth scattered light from the material responsive to thesecond light during a fourth time window having the second duration, thefourth scattered light having little Raman signal, the fourth scatteredlight having the second wavelength; detecting a peak intensity of thefourth scattered light; recovering a spectrum of the material by takinga ratio of the peak intensity of the first scattered light and the peakintensity of the second scattered light, and taking a ratio of the peakintensity of the third scattered light and the peak intensity of thefourth scattered light; and identifying at least one molecule of thematerial using the recovered spectrum and a database of identifiedspectra.

BRIEF DESCRIPTION OF THE DRAWINGS

Embodiments are illustrated by way of example, and not by limitation, inthe figures of the accompanying drawings, in which like referencesindicate similar elements and in which:

FIG. 1 is a simplified representation of a system for fluorescence andsystematic noise reduction in time-gated spectroscopy, according to someembodiments.

FIG. 2 is a simplified representation of a spectrum, according tovarious embodiments.

FIGS. 3A and 3B illustrate fluorescence, in accordance with someembodiments.

FIG. 4 illustrates fluorescence and systematic noise, in accordance withvarious embodiments.

FIG. 5 is a simplified representation of spectra taken during differentwindows of time, according to some embodiments.

FIGS. 6A and 6B are simplified representations of spectra withfluorescence and systematic noise removed, according to variousembodiments.

FIG. 7 is a simplified flow diagram of a method for systematic noisereduction in time-gated spectroscopy, in accordance with someembodiments.

FIG. 8 is a simplified comparison of spectra, in accordance with variousembodiments.

FIG. 9 is a simplified block diagram of a computing system, according tosome embodiments.

DETAILED DESCRIPTION

While this technology is susceptible of embodiment in many differentforms, there is shown in the drawings and will herein be described indetail several specific embodiments with the understanding that thepresent disclosure is to be considered as an exemplification of theprinciples of the technology and is not intended to limit the technologyto the embodiments illustrated. The terminology used herein is for thepurpose of describing particular embodiments only and is not intended tobe limiting of the technology. As used herein, the singular forms “a,”“an,” and “the” are intended to include the plural forms as well, unlessthe context clearly indicates otherwise. It will be further understoodthat the terms “comprises,” “comprising,” “includes,” and/or“including,” when used in this specification, specify the presence ofstated features, integers, steps, operations, elements, and/orcomponents, but do not preclude the presence or addition of one or moreother features, integers, steps, operations, elements, components,and/or groups thereof. It will be understood that like or analogouselements and/or components, referred to herein, may be identifiedthroughout the drawings with like reference characters. It will befurther understood that several of the figures are merely schematicrepresentations of the present technology. As such, some of thecomponents may have been distorted from their actual scale for pictorialclarity.

FIG. 1 illustrates system 100 for fluorescence and systematic noisereduction according to some embodiments. System 100 can includespectrometer 110, material 150, and computing system 190.

According to some embodiments, material 150 is at least one of solid,liquid, plant tissue, human tissue, and animal tissue. Generally,material 150 has fluorescence or phosphorescence background emissionswhen illuminated by spectrometer 110. For example, animal tissue is oneor more of epithelial, nerve, connective, muscle, and vascular tissues.By way of further non-limiting example, plant tissue is one or more ofmeristematic (e.g., apical meristem and cambium), protective (e.g.,epidermis and cork), fundamental (e.g., parenchyma, collenchyma andsclerenchyma), and vascular (e.g., xylem and phloem) tissues.

According to some embodiments, spectrometer 110 comprises excitationlight source 120, optical bench 130, optional sampling apparatus 140,and delay 180. Excitation light source 120 is a monochromatic lightsource, such as a laser, in accordance with some embodiments. Forexample, excitation light source 120 is at least one of an Nd:YAG(neodymium-doped yttrium aluminum garnet; Nd:Y3Al5O12), Argon-ion,He—Ne, and diode laser. By way of further non-limiting example,excitation light source 120 can provide light (electromagnetic waves) ina range between ultra-violet (UV) light (e.g., electromagnetic radiationwith a wavelength from 10 nm to 400 nm) and shortwave near-infrared(NIR) (1.4 μm to 3 μm), including portions of the electromagneticspectrum in-between, such as visible light (e.g., 380 nm-760 nm) and NIRlight (e.g., 0.75 μm to 1.4 μm).

In various embodiments, excitation light source 120 is tunable—awavelength of the light from excitation light source 120 is changed byone or more (predetermined) increments and/or to one or more(predetermined) values—such as by using heat control (e.g., from aheating element), electrical control (e.g., using microelectromechanicalsystems (MEMS)), and mechanical control (e.g., using a mechanism to turna mirror). Preferably, excitation light source 120 provides highspectral purity, high wavelength stability, and/or high power stabilityoutput.

Optional sampling apparatus 140 performs various combinations andpermutations of directing light 160 from excitation light source 120,collecting the resulting Raman scattered light or Raman scatter (amongothers) 170, filtering out radiation at the wavelength corresponding tothe laser line (e.g., Rayleigh scattering), and providing the Ramanscatter (among others) 170 to optical bench 130, according to someembodiments. For example, optional sampling apparatus 140 includes amicroscope and/or an optical probe. By way of further non-limitingexample, optional sampling apparatus 140 includes optical fiber, one ormore filters (e.g., notch filter, edge-pass filter, and band-passfilter), and the like. Raman scatter (among others) 170 includes, forexample, at least one of Raman scatter, fluorescence, and Rayleighscattering (which can be filtered out by sampling apparatus 140).

In accordance with some embodiments, optical bench 130 is aspectrograph. For example, optical bench 130 includes slit 132, spectraldispersion element 134, and detector 136. By way of non-limitingexample, optical bench 130 measures wavelengths in one or more of the UVspectrum (10 nm to 400 nm), visible spectrum (e.g., 380 nm-760 nm),visible to near-infrared (e.g., 400 nm-1000 nm), short-wave infrared(e.g., 950 nm-1700 nm), and infrared (e.g., 1 μm-5 μm).

Slit 132, spectral dispersion element 134, and detector 136 can bearranged in optical bench 138, along with other components (e.g.,monochromater—which transmits a mechanically selectable narrow band ofwavelengths of light or other radiation chosen from a wider range ofwavelengths available at an input—including one or more of a mirror,prism, collimater, holographic grating, diffraction grating, blazedgrating, and the like), according to different configurations. Forexample, different configurations include: crossed Czerny-Turner,unfolded Czerny-Turner, transmission, and concave holographic opticalbenches.

Slit 132 can determine the amount of light (e.g., photon flux, such asRaman scatter (among others) 170) that enters optical bench 138.Dimensions (e.g., height and width, not shown in FIG. 1) of slit 132 candetermine the spectral resolution of optical bench 130. By way ofnon-limiting example, a height of slit 132 can range from 1 mm to 20 mm.By way of further non-limiting example, a width of slit 132 can rangefrom 5 μm to 800 μm.

Spectral dispersion element 134 can determine a wavelength range ofoptical bench 130 and can partially determine an optical resolution ofoptical bench 130. For example, spectral dispersion element 134 is aruled diffraction grating or a holographic diffraction grating, in theform of a reflective or transmission package. Spectral dispersionelement 134 can include a groove frequency and a blaze angle.

Detector 136 receives light and measures the intensity of scatteredlight. Detector 136 can be a one- or two-dimensional detector arraycomprised of a semiconductor material such as silicon (Si) and indiumgallium arsenide (InGaAs). In some embodiments, a bandgap energy of thesemiconductor determines an upper wavelength limit of detector 136. Anarray of detector 136 can be in different configurations, such ascharged coupled devices (CCDs), back-thinned charge coupled devices(BT-CCDs), complementary metal-oxide-semiconductor (CMOS) devices, andphotodiode arrays (PDAs). CCDs can be one or more of intensified CCDs(ICCDs) with photocathodes, back illuminated CCDs, and CCDs with lightenhancing coatings (e.g., Lumogen® from BASF®). Detector 136 has aresolution of 8-15 wavenumbers, according to some embodiments. Detector136 can be used to detect concentrations of molecules in the range of1-1,000 mg per deciliter (mg/dL).

By way of further non-limiting example, detector 136 is a single pixeltime-gated detector such as single-photon avalanche diode (SPAD),micro-channel plate (MCP), photomultiplier tube (PMT), siliconphotomultiplier (SiPM), or avalanche photodiode (APD) that sits on ascanning motor driven rail, or detector arrays such as a single-photonavalanche diode (SPAD) array, or an intensified CCD (ICCD). A SPAD is asolid-state photodetector in which a photon-generated carrier (via theinternal photoelectric effect) can trigger a short-duration butrelatively large avalanche current. The leading edge of the avalanchepulse marks the arrival (time) of the detected photon. The avalanchecurrent can continue until the avalanche is quenched (e.g., by loweringa bias voltage down to a breakdown voltage). According to variousembodiments, each pixel in some SPAD arrays can count a single photonand the SPAD array can provide a digital output (e.g., a 1 or 0 todenote the presence or absence of a photon for each pixel).

To detect another photon, a control circuit(s) (not depicted in FIG. 1)integrated in and/or external to the SPAD can be used to read outmeasurements and quench the SPAD. For example, the control circuit cansense the leading edge of the avalanche current, generate a (standard)output pulse synchronous with the avalanche build up, quench theavalanche, and restore the diode to an operative level. The controlcircuit can provide passive quenching (e.g., passive quenching passivereset (PQPR), passive quench active reset (PQAR), and the like) and/oractive quenching (e.g., active quench active reset (AQAR), activequenching passive reset (AQPR), and the like). In various embodiments,detector 136A is a complementary metal-oxide semiconductor (CMOS) SPADarray.

A micro-channel plate (MCP) is a planar component used for detection ofsingle particles, such as photons. An MCP can intensify photons by themultiplication of electrons via secondary emission. Since a microchannelplate detector has many separate channels, it can also provide spatialresolution.

A photomultiplier tube (PMT) is a photoemissive device which can detectweak light signals. In a PMT, absorption of a photon results in theemission of an electron, where the electrons generated by a photocathodeexposed to a photon flux are amplified. A PMT can acquire light througha glass or quartz window that covers a photosensitive surface, called aphotocathode, which then releases electrons that are multiplied byelectrodes known as metal channel dynodes. At the end of the dynodechain is an anode or collection electrode. Over a very large range, thecurrent flowing from the anode to ground is directly proportional to thephotoelectron flux generated by the photocathode.

Silicon photomultipliers (SiPM) are solid-state single-photon-sensitivedevices based on Single-photon avalanche diode (SPAD) implemented on acommon silicon substrate. Each SPAD in an SiPM can be coupled with theothers by a metal or polysilicon quenching resistor.

Avalanche photodiodes (APDs) are semiconductor photodiodes with aninternal gain mechanism. In an APD, absorption of incident photonscreates electron-hole pairs. A high reverse bias voltage creates astrong internal electric field, which accelerates the electrons throughthe semiconductor crystal lattice and produces secondary electrons byimpact ionization. The resulting electron avalanche can produce gainfactors up to several hundred.

An intensified charge-coupled device (ICCD) is a CCD that is opticallyconnected to an image intensifier that is mounted in front of the CCD.An image intensifier can include three functional elements: aphotocathode, a micro-channel plate (MCP) and a phosphor screen. Thesethree elements can be mounted one close behind the other. The photonswhich are coming from the light source fall onto the photocathode,thereby generating photoelectrons. The photoelectrons are acceleratedtowards the MCP by an electrical control voltage, applied betweenphotocathode and MCP. The electrons are multiplied inside of the MCP andthereafter accelerated towards the phosphor screen. The phosphor screenconverts the multiplied electrons back to photons which are guided tothe CCD by a fiber optic or a lens. An image intensifier inherentlyincludes shutter functionality. For example, when the control voltagebetween the photocathode and the MCP is reversed, the emittedphotoelectrons are not accelerated towards the MCP but return to thephotocathode. In this way, no electrons are multiplied and emitted bythe MCP, no electrons are going to the phosphor screen, and no light isemitted from the image intensifier. In this case no light falls onto theCCD, which means that the shutter is closed.

Detector 136 can be other photodetectors having a time resolution ofabout one nanosecond or less. By way of further non-limiting example,detector 136 is a streak camera array, which can have a time-resolutionof around 180 femtoseconds. A streak camera measures the variation in apulse of light's intensity with time. A streak camera can transform thetime variations of a light pulse into a spatial profile on a detector,by causing a time-varying deflection of the light across the width ofthe detector.

A spectral resolution of a spectrum measured by detector 136 can dependon the number of pixels (e.g., discrete photodetectors) in detector 136.A greater number of pixels can provide a higher spectral resolution.Detector 136 can comprise a one-dimensional and/or two-dimensional arrayof pixels. For example, detector 136 has in a range of 32 to 1,048,576pixels. According to some embodiments, detector 136 has in a range of512 to 1,024 pixels.

In some embodiments, the output (e.g., measurements) from detector 136is provided to an analog-to-digital converter (ADC) (not shown in FIG.1). The ADC can be integrated into detector 136 or separate fromdetector 136, such as in at least one of optical bench 130, spectrometer110, and computing system 190. The ADC can convert the measurementsbefore the next measurements are received. For example, whenmeasurements are received at 20 kHz, the ADC can convert at 20 kHz orfaster. When the output of detector 136 is already a digital spectra,analog-to-digital conversion is not needed.

Spectrometer 110 can provide information about molecular vibrations toidentify and quantify characteristics (e.g., molecules) of material 150.Spectrometer 110 can direct light (electromagnetic waves) 160 fromexcitation light source 120 (optionally through optional samplingapparatus 140) onto material 150. Light 160 from excitation light source120 can be said to be shone on material 150 and/or material 150 can besaid to be illuminated by excitation light source 120 and/or light 160.When (incident) light from excitation light source 120 hits material150, the (incident) light scatters. A majority (e.g., 99.999999%) of thescattered light is the same frequency as the light from excitation lightsource 120 (e.g., Rayleigh or elastic scattering).

A small amount of the scattered light (e.g., on the order of 10⁻⁶ to10⁻⁸ of the intensity of the (incident) light from excitation lightsource 120) is shifted in energy from the frequency of light 160 fromexcitation light source 120. The shift is due to interactions between(incident) light 160 from excitation light source 120 and thevibrational energy levels of molecules in material 150. (Incident) Light160 interacts with molecular vibrations, phonons, or other excitationsin material 150, causing the energy of the photons (of light 160 fromexcitation light source 120) to shift up or down (e.g., Raman orinelastic scattering). The shift in energy (e.g., of Raman scatter 170from material 150) can be used to identify and quantify characteristics(e.g., molecules) of material 150.

Optical bench 130 detects (an intensity of) the Raman scatter 170 usingdetector 136 (optionally received through optional sampling apparatus140).

Spectrometer 110 can further include delay 180 for gating, according tosome embodiments. Delay 180 can be communicatively coupled to excitationlight source 120 and detector 136 through communications 185. In variousembodiments, delay 180 can detect when excitation light source 120provides light 160 (e.g., a laser pulse is emitted). For example, delay180 can have a sensor (not depicted in FIG. 1) which detects light 160being emitted from excitation light source 120. By way of furthernon-limiting example, excitation light source 120 can provide a(electronic) signal to delay 180 when excitation light source 120provides light 160 (e.g., fires laser pulse). A predetermined amount oftime after light 160 is detected/signaled, delay 180 can provide asignal indicating to detector 136 to (effectively) stop detecting andprovide measurements (e.g., report a photon count at that time). Thepredetermined amount of time can be a gate (e.g., time window 330 andtime window 340 in FIG. 3A). For example, the predetermined amount oftime (e.g., gate or time window) can be selected using the duration oflight 160 (e.g., a laser pulse), characteristics of the material beingmeasured (e.g., duration/lifetime of fluorescence), and the like.

Delay 180 can be an (programmable) analog (e.g., continuous time) and/ordigital (e.g., discrete time) delay line. In some embodiments, delay 180is a network of electrical components connected in series, where eachindividual element creates a time difference between its input signaland its output signal. In various embodiments, delay 180 comprises oneor more delay elements (e.g., forming a (circular) buffer) such as indiscrete logic (e.g., flip flops, inverters, digital (or voltage)buffer, and the like), (general purpose) microprocessor, digital signalprocessor, application specific standard product (ASSP),application-specific integrated circuit (ASIC), field-programmable gatearray (FPGA), and the like. Although depicted as a part of spectrometer110, delay 180 can alternatively be external to spectrometer 110, suchas part of computing system 190.

Spectrometer 110 can be communicatively coupled to computing system 190through communications 195. Communications 195 can be variouscombinations and permutations of wired and wireless communications(e.g., networks) described below in relation to FIG. 9. Computing system190 can include a database of Raman spectra associated with knownmolecules and/or remotely access the database over a communicationsnetwork (not shown in FIG. 1). In some embodiments, computing systemreceives intensity measurements from spectrometer 110, produces at leastone Raman spectrum using data (e.g., intensity measurements) fromspectrometer 110, and identifies and/or quantifies molecules in material150 using the at least one Raman spectrum and a database of Ramanspectra associated with known molecules.

In some embodiments, computing system 190 is a single computing device.For example, computing system 190 is a desktop or notebook computercommunicatively coupled to Spectrometer 110 through a Universal SerialBus (USB) connection, a WiFi connection, and the like.

In various embodiments, computing system 190 can be various combinationsand permutations of stand-alone computers (e.g., smart phone, phablet,tablet computer, notebook computer, desktop computer, etc.) andresources in a cloud-based computing environment. For example, computingsystem 190 is a smart phone and a cloud-based computing system. Thesmart phone can receive data (e.g., intensity measurements) fromspectrometer 110 using USB, WiFi, Bluetooth, and the like. The smartphone can optionally produce at least one Raman spectrum (e.g.,including the Raman signal and fluorescence, for each excitationwavelength) using the data. The smart phone can transmit the data and/orat least one Raman spectrum to a cloud-based computing system over theInternet using a wireless network (e.g., cellular network). Thecloud-based computing system can produce at least one Raman spectrumusing the data, recover Raman spectrum (e.g., without fluorescence andsystematic noise) from the at least one received/produced Ramanspectrum, and/or quantify and/or identify molecules in material 150using the recovered Raman spectrograph. Although depicted as outside ofspectrometer 110, additionally or alternatively at least part ofcomputer system 190 can be integrated into spectrometer 110. Computingsystem 190 is described further in relation to FIG. 9.

According to some embodiments, spectrometer 110 offers at least some ofthe advantages of: differentiating chemical structures (even if theycontain the same atoms in different arrangements), physical contact withmaterial 150 not required, no damage to material 150 (e.g.,non-destructive testing), preparation of material 150 is not required,material 150 can be in a transparent container (e.g., when light 160 isin the visible or near-visible light spectrum), sensitivity to smallchanges in material structure (e.g., detection of molecular vibrationsis very sensitive to changes in chemistry and structure), analyzingsamples in aqueous solutions (e.g., suspensions, biological samples,etc.), and the like.

FIG. 2 illustrates example spectrum 200 produced using system 100 (FIG.1). A Raman spectrum—a plot/graph of an intensity of the Ramanscattering (shifted light) against frequency—can be produced by acomputing system 190 using intensity measurements from optical bench130. Spectrum 200 (and 250A) can reliably be used to identify moleculesin material 150. In this way, Raman spectra (e.g., spectra 250A) can besaid to produce a “fingerprint” of molecules in material 150. Forexample, Raman spectra (e.g., spectra 250A) of material 150 can becompared to a database (e.g., in the same or another computing system)of Raman spectra associated with known molecules to identify andquantify molecules in material 150.

Spectrum 200 are plotted/graphed along three axes: intensity 210A, time220A, and wavelength A (or wavenumber) 230A. As shown in FIG. 2,intensity (axis 210A) can be power (light intensity) in a.u. (arbitraryunits of intensity); other units can be milliwatts (mW) or photon count.Time (axis 220A) can be in nanoseconds (ns). Wavelength (axis 230A) canbe a Raman shift in units such as nanometers (nm) or as a wavenumber incm⁻¹. System 100 can measure an intensity of Raman scatter havingwavelength A. For example, measurements taken at three wavelengths λ₁,λ₂, and λ₃ result in measurements 240A₁, 240A₂, and 240A₃, respectively.Measurements 240A₁, 240A₂, and 240A3 show an intensity of Ramanscattered light (the light having a particular wavelength λ₁, λ₂, andλ₃) over time. Each of measurements 240A₁-240A₃ can be individuallyviewed when plotted/graphed along two axes: intensity 210A and time220A. Measurements 240A₁-240A₃ can be collectively viewed whenplotted/graphed along two axes: intensity 210A and wavelength λ (orwavenumber) 230A, which results in spectrum 250A (which can be referredto as a Raman spectrum). Spectrum 250A shows the peak intensity of Ramanscatter at a range of wavelengths λ, such as wavelengths λ₁, λ₂, and λ₃(or wavenumber).

FIG. 3A shows graphical representation (e.g., plot, graph, and the like)300A of (relative) (received) light intensity or power (e.g., inarbitrary units of intensity (a.u.), in milliwatts (mW), or photoncount) along axis 210B over time (e.g., in nanoseconds) along axis 220B.Graphical representation 300A includes Raman signal 310A, fluorescence320A, and total signal 240B, according to some embodiments. Raman signal310A is, by way of non-limiting example, an intensity of a particularwavelength of Raman scatter for a material to be measured (e.g.,material 150 in FIG. 1). Total signal 240B can have at least some of thecharacteristics of spectra 240A₁-240A₃ (FIG. 2) and be an intensitymeasured by a detector (e.g., optical bench 130 in FIG. 1) from(approximately) time t₀ to time t₄. In contrast to Raman scattering,fluorescence emission (fluorescence 320A) follows an absorption process.Fluorescence 320A can be several orders of magnitude (e.g., 10⁵-10⁶)higher in intensity than Raman signal 310A and can overwhelm or obscureRaman signal 310A, such that Raman signal 310A is difficult to measure.

When light (e.g., light 160 in FIG. 1) from an excitation source (e.g.,excitation light source 120 in FIG. 1) illuminates a material to bemeasured (e.g., material 150 in FIG. 1), receipt of the Raman signal(also called Raman scatter or return signal) 310A by a detector (e.g.,detector 136 in FIG. 1) is almost instantaneous (e.g., ≤1 ps, dependingon the distance travelled by the light and the Raman signal) (e.g., attime t₀). For this reason, Raman signal 310A can also be thought of as(approximately) representing the light from the excitation source, suchas a laser pulse. In contrast, fluorescence 320A is received/occursafter Raman signal 310A (e.g., at time t₁). When light from theexcitation source illuminates the material to be measured (e.g., at timet₀), receipt of fluorescence 320A by the detector occurs later (e.g., attime t₁, which can be hundreds of nanoseconds or even millisecondslater).

When the detector (e.g., detector 136 in FIG. 1) is active (e.g.,measuring light, detecting photons, and the like) while Raman signal310A is present and before fluorescence 320A obscures/interferes withRaman signal 310A (e.g., from time t₀ to time t₂), Raman signal 310A canbe measured by the detector without being completely overwhelmed orobscured by fluorescence 320A. Time window 330 is ideally narrow(relative to time window 340) and the time during which most (90%-100%)of the Raman photons are present and can be collected, although inpractice time window 330 can be broader to include time when Ramanphotons are not present. For example, time window 330 is as wide(time-wise) as a laser pulse from excitation light source 120 (FIG. 1)(e.g., t₀-t₃). By way of further example, time window 330 is the timeduring which Raman signal 310A is present (e.g., approximately 80%-100%of peak intensity) and fluorescence 320A is mostly not present (e.g.,from time t₀ to time t₂, time t₀ to time t₃, and the like) or ispresent.

As shown in FIG. 3A, although fluorescence 320A begins being received attime t₁, an intensity of fluorescence 320A may not be high enough tobegin overwhelm or obscure Raman signal 310 until at or after time t₂.Control of the detector such that the detector is substantially activeonly during time window 330 can be referred to as gating. Moreover, timewindow 330 can also be referred to as gate 330. Gating can be used toreject a significant portion of fluorescence 320A.

In some embodiments, the detector (e.g., detector 136 in FIG. 1) isactive (e.g., gate 330 in FIG. 3A begins) prior to the excitation source(e.g., excitation light source 120 in FIG. 1) providing light. By way ofnon-limiting example, (ideal) gate 330 is 1 ns (1,000 ps). The timeresolution of the detector using the 1 ns (ideal) gate 330 isapproximately equal to the laser pulse duration (e.g., 600 ps).

Time window 340 is a second time window or gate which is ideallybroad/wide (relative to time window 330) and during which Raman photonsare ideally not present and not detected, and fluorescence is present.In practice, Raman photons may be present during time window 340. Forexample, during time window 340, little of Raman signal 310A is present(e.g., 0%-20% of peak intensity).

As shown in FIG. 3A, time window 340 can partially (or completely)overlap with time window 330. Alternatively, time window 330 and timewindow 340 can be contiguous. In other words, time window 330 and timewindow 340 occur one after the other sequentially. For example, timewindow 340 can begin (almost immediately) after time window 330 ends,and can end before the intensity of total signal 240 drops to zero(e.g., at time t₄). For example, time window 340 can extend out to timet₄. In various embodiments, time window 330 ends and time window 340begins before or after t₁ (or t₂). Generally, time window 330 is shorterin duration than time window 340, although time window 330 can begreater-than-or-equal-to time window 340.

The spectrometer (e.g., spectrometer 110) can be controlled such thatmeasurements can be taken during both time window 330 and time window340 using one pulse (e.g., of light from excitation light source 120).Alternatively or additionally, two pulses (e.g., of light fromexcitation light source 120), one pulse for measurements in time window330 and another pulse during time window 340.

FIG. 3B depicts graphical representation (e.g., plot, graph, and thelike) 300B of (relative) (received) light intensity or power (e.g., inarbitrary units of intensity (a.u.), in milliwatts (mW), or photoncount) (along axis 210C) over time (e.g., in nanoseconds) along axis220C from a (e.g., 600 ps) laser pulse, in accordance with someembodiments. Graphical representation 300B can include Raman signal 310Band fluorescence 320B₁-320B₃. Graphical representation 300B can showrelative intensities and/or lifetimes/durations of Raman signal 310B andfluorescence 320B₁-320B₃. Raman signal 310B has at least some of thecharacteristics of Raman signal 310A described above in relation to FIG.3A. Fluorescence 320B₁-320B₃ can have at least some of thecharacteristics of fluorescence 320A (FIG. 3A). Since Raman scatteringoccurs almost immediately (e.g., ≤1 ps, depending on the distancetravelled by the light and the Raman signal) after an excitation lightpulse from the excitation source (e.g., excitation light source 120 inFIG. 1), Raman signal 310B can also (approximately) represent theexcitation light pulse.

Graphical representation 300B illustrates the relative intensitiesand/or the relative lifetimes/durations among fluorescence 320B₁-320B₃,according to various embodiments. Raman signal 310B can have at leastsome of the characteristics of Raman signal 310A (FIG. 3A). Fluorescence320B₁-320B₃ can have at least some of the characteristics offluorescence 320A (FIG. 3A). In some embodiments, fluorescence320B₁-320B₃ results when light (e.g., light 160 in FIG. 1) from anexcitation source (e.g., excitation light source 120 in FIG. 1)illuminates a material to be measured (e.g., material 150 in FIG. 1),where the wavelength of the light used varies. In other words,fluorescence 320B₁-320B₃ can be from the same material, but thewavelength of the light used is different.

As shown in FIG. 3B, each of fluorescence 320B₁-320B₃ can have adifferent lifetime/duration, with fluorescence 320B₁ having the shortestand fluorescence 320B₃ having the longest. By way of non-limitingexample, fluorescence 320B₁ has a 1 ns lifetime/duration, fluorescence320B₂ has a 5 ns lifetime/duration, and fluorescence 320B₃ has a 10 nslifetime/duration. Depending upon the material, a fluorescence can haveother lifetimes/durations (e.g., 100 ps-10 ms). As shown in FIG. 11B,the longer the lifetime/duration of a respective one of fluorescence320B₁-320B₃, the lower the intensity of a respective one of fluorescence320B₁-320B₃ can be. Moreover, the decay rate of fluorescence 320B₁-320B₃is different at each frequency.

FIGS. 4A and 4B depict fluorescence, and fluorescence and systematicnoise (respectively) in a Raman spectrum. FIG. 4A is a graphicalrepresentation (e.g., plot, graph, and the like) 400A of (relative)(received) light intensity or power (e.g., in arbitrary units ofintensity (a.u.), in milliwatts (mW), or photon count) along axis 210D₁over wavelength (e.g., in nm) (or wavenumber in cm⁻¹) along axis 230B₁,according to some embodiments. Raman signal 410 ₁ is, by way ofnon-limiting example, an intensity of Raman scatter for a material to bemeasured (e.g., material 150 in FIG. 1). Spectrum 250B₁ can have atleast some of the characteristics of spectrum 250A (FIG. 2). Spectrum250B₁ includes Raman signal 410 ₁ and fluorescence (e.g., fluorescence320A (FIG. 3A) and fluorescence 320B₁-320B₃ (FIG. 3B). Although,fluorescence can be can be several orders of magnitude (e.g. 10⁵-10⁶)higher in intensity than Raman signal 410 ₁, Raman signal 410 ₁ canstill be discerned as peak 420 ₁ in spectrum 250B₁.

FIG. 4B is a graphical representation (e.g., plot, graph, and the like)400B of (relative) (received) light intensity or power (e.g., inarbitrary units of intensity (a.u.), in milliwatts (mW), or photoncount) along axis 210D₂ over wavelength (e.g., in nm) (or wavenumber incm⁻¹) along axis 230B₂, according to various embodiments. Raman signal410 ₂ is, by way of non-limiting example, an intensity of Ramanscattered light for a material to be measured (e.g., material 150 inFIG. 1). Spectrum 250B₂ can have at least some of the characteristics ofspectrum 250A (FIG. 2). Spectrum 250B₂ includes Raman signal 410 ₂,fluorescence (e.g., fluorescence 320A (FIG. 3A) and fluorescence320B₁-320B₃ (FIG. 3B)), and systematic noise. Systematic noise arisesfrom components (e.g., etalon, grating, reflector, filter, and the like)of a spectrometer (e.g., spectrometer 110 in FIG. 1) which can havemultiple reflections that interfere with each other to produce aninterference pattern, creating a periodic fluctuation in the spectrum.In contrast to spectrum 250B₁, the systematic noise in spectrum 250B₂obscures peak 420 ₂, which is an indication of Raman signal 410 ₂.

FIG. 5 illustrates graphical representation (e.g., plot, graph, and thelike) 500 of (relative) (received) light intensity or power (e.g., inarbitrary units of intensity (a.u.), in milliwatts (mW), or photoncount) along axis 210E over wavelength (e.g., in nm) (or wavenumber incm⁻¹) along axis 230C, in accordance with some embodiments. Graphicalrepresentation 500 includes spectrum 250C₁ and spectrum 250C₂. Spectrum250C₁ and spectrum 250C₂ can have at least some of the characteristicsdescribed above for spectrum 250A (FIG. 2), and spectrum 420 ₁ andspectrum 420 ₂ (FIG. 4).

As shown in FIG. 5, spectrum 250C₁ and spectrum 250C₂ go up from left toright, which can generally be ascribed to the change in fluorescenceover wavelength, such as described in relation to FIG. 3B. In someembodiments, measurements shown in spectrum 250C₁ can be made in a timewindow (or gate) when for the most part a Raman signal is present andfluorescence is not present (e.g., time window 330 in FIG. 3A). Systemicnoise (described in relation to FIG. 4) is present in both spectrum250C₁ and spectrum 250C₂. Measurements shown in spectrum 250C₂ can bemade in a time window (or gate) when for the most part a Raman signal isnot present and fluorescence is present (e.g., time window 340 in FIG.3A). Generally, spectrum 250C₂ can have a lower intensity than spectrum250C₁, at a particular wavelength, since the intensity of fluorescencemay have decayed by/in time window 340 (FIG. 3A) relative to time window330.

To reduce systemic noise and fluorescence and to recover a Ramanspectrum, measurements made in time window 330 (FIG. 3A) (e.g., spectrum250C₁ in FIG. 5) can be divided by measurements made in time window 340(e.g., spectrum 250C₂). This calculation relies upon certainassumptions. For example, this calculation assumes that systemic noiseis not random. By way of further example, this calculation assumes thatthe amplitude of systemic noise is linearly proportional to an amplitudeof fluorescence (plus Raman signal). In other words, if the amplitude offluorescence (plus Raman signal) increases by a factor of 10 (at aparticular wavelength) from spectrum 250C₂ to spectrum 250C₁, thensystemic noise increases by a factor of 10 (at that wavelength), aswell.

FIGS. 6A and 6B illustrate graphical representations (e.g., plot, graph,and the like) 600A and 600B of (relative) (received) power (lightintensity) in a.u. (arbitrary units of intensity) (other units can bemilliwatts (mW) or photon count) along axis 210F over wavelength aswavenumber in cm⁻¹ (other units can be nm) along axis 230D, inaccordance with some embodiments. Graphical representation 500 includesrecovered Raman spectrum 250D. For example, recovered Raman spectrum250D results from dividing spectrum 250C₁ (FIG. 5) (e.g., measurementsmade in time window 330 (FIG. 3A) by spectrum 250C₂ (e.g., measurementsmade in time window 340 (FIG. 3A)).

As shown in FIG. 6A, recovered Raman spectrum 250D goes up from left toright, which can generally be attributed to the change in fluorescenceover wavelength, such as described in relation to FIG. 3B. To minimizethis effect (e.g., normalize recovered Raman spectrum 250D), recoveredRaman spectrum 250D can optionally be fit to curve 610, and (pointsalong) curve 610 can be subtracted from (corresponding points along)recovered Raman spectrum 250D. Curve 610 can serve as a baseline (and bereferred to as a baseline) for recovered Raman spectrum 250D. Curve 610can be calculated from recovered Raman spectrum 250D, for example, usinga simple linear regression (where curve 610 is a straight line),third-order polynomial curve fitting (where curve 610 is a polynomialcurve), and the like. For two-dimensional sample points with oneindependent variable and one dependent variable (e.g., the x- andy-coordinates in a Cartesian coordinate system), a simple linearregression determines a linear function (a non-vertical straight line)that predicts the dependent variable values as a function of theindependent variables. Curve fitting constructs a curve (or mathematicalfunction), that has the best fit to a series of data points, possiblysubject to constraints. Curve fitting can involve either interpolation(where an exact fit to the data is required) or smoothing (in which a“smooth” function is constructed that approximately fits the data).

FIG. 6B illustrates a normalized recovered Raman spectrum 250E.Normalized recovered Raman spectrum 250E can be computed, for example,by subtracting (points along) curve 610 (FIG. 6A) from (correspondingpoints along) recovered Raman spectrum 250D.

FIG. 7 illustrates method 700 for reducing fluorescence and systemicnoise in time-gated Raman spectroscopy, according to some embodiments.Method 700 can be performed by spectrometer 110 and computing system 190(FIG. 1). According to various embodiments, steps 710-750 illuminate amaterial and measure an intensity of Raman scatter over a range ofwavelengths (e.g., λ₀-λ_(N-1)). The measurements at each excitationwavelength are taken twice: during a first time window (e.g., duringwhich there is a substantial Raman signal) and a second time window(e.g., during which there is a small amount of Raman signal). Anon-limiting example of measurements collectively taken using steps710-750 can be graphically represented as shown in and described inrelation to FIG. 5.

Method 700 can commence at step 710, where a material can beilluminated. In some embodiments, light such as a laser pulse providedby excitation light source 120 (FIG. 1) is directed at a material. Thematerial can have at least some of the characteristics of material 150(FIG. 1). For example, a laser pulse is provided to take measurements ata particular wavelength.

At step 720, an (peak) intensity of Raman scatter from the material,fluorescence from the material, and systemic noise from an element inthe spectrometer are collectively detected for an initial wavelengthduring two time windows (gates). For example, measurements are takenduring time window 330 and time window 340 (FIG. 3A), separately. Insome embodiments, the light hitting the material results in Ramanscatter (or Raman signal) and fluorescence. For example, the Ramanscatter, fluorescence, and systemic noise (which can arise from anelement in spectrometer 110 (FIG. 1)) can be detected by spectrometer110. By way of further non-limiting example, the detected Raman scatterand fluorescence may appear over time (e.g., when graphed, plotted, andthe like) as total signal 240B in graphical representation 300A (FIG.3A). The measured (peak) intensity of the Raman scatter (e.g., data,graphical representation, and the like) can be stored in spectrometer110 and/or the computing system 190.

At step 730, the material can be optionally illuminated. In someembodiments, light such as a laser pulse is provided by excitation lightsource 120 (FIG. 1). For example, a laser pulse is provided formeasurements at a particular wavelength or wavelengths. Alternatively oradditionally, measurements at step 740 can be made using a differentpart (e.g., pixels) of a detector (e.g., detector 136 in FIG. 1) usingthe light from step 710 (hence light at step 730 is optional). In thisway, steps 720 and at least some iterations of step 740 can be performedin parallel.

At step 740, an (peak) intensity of Raman scatter from the material,fluorescence from the material, and systemic noise from an element inthe spectrometer are collectively detected for an initial wavelengthduring two time windows (gates). For example, measurements are takenduring time window 330 and time window 340 (FIG. 3A), separately. By wayof further non-limiting example, the measurements can be representedgraphically as shown in FIG. 5.

At step 750, a determination is made as to whether another measurementis to be made. In some embodiments, the predetermined number (N) ofmeasurements to be made is compared to the number of measurements(already) made. When the predetermined number (N) of measurements to bemade is less than the number of measurements (already) made, method 700can proceed to step 730. For example, when N=8 and measurements are onlytaken for wavelengths λ₀, λ₁, λ₂, λ₃, λ₄, and λ₅, method 700 can proceedto step 730. When the predetermined number (N) of measurements to bemade is equal to the number of measurements (already) made, method 700can proceed to step 760. For example, when N=6 and measurements arealready taken for wavelengths λ₀, λ₁, λ₂, λ₃, λ₄, and λ₅, method 700 canproceed to step 760.

At step 760, two spectra can be constructed. For example, the peakintensities (e.g., N measurements) over wavelength measured during timewindow 330 (FIG. 3A) comprise a first spectra (e.g., graphicallydepicted as spectrum 250C₁ in FIG. 5). By way of further non-limitingexample, the peak intensities (e.g., N measurements) over wavelengthmeasured during time window 340 (FIG. 3A) comprise a second spectra(e.g., graphically depicted as spectrum 250C₂ in FIG. 5).

At step 770, a Raman spectrum of the material can be recovered (e.g.,the fluorescence and systematic noise are reduced enough to discern thepeaks of Raman scatter) using the two constructed spectra. In someembodiments, the Raman spectrum of the material can be recovered usingthe first spectra (e.g., peak intensities during a time window 330 (FIG.3A)) and the second spectra (e.g., peak intensities during time window340). For example, the first spectra can be divided by the secondspectra to produce the recovered Raman spectrum. For example, therecovered Raman spectrum may appear (e.g., when graphed/plotted) asrecovered Raman spectrum 250D in FIG. 6.

Optionally at step 780, the recovered Raman spectrum can be normalized.For example, the recovered Raman spectrum (e.g., recovered Ramanspectrum 250D in FIG. 6) can be fit to curve 610, and (points along)curve 610 can be subtracted from (corresponding points along) recoveredRaman spectrum 250D. This normalization process is described further inrelation to FIG. 6.

Optionally at step 790, a molecule can be identified using the recoveredRaman spectrum (and/or normalized recovered Raman spectrum). Forexample, a database of known Raman spectra for certain molecules can besearched using (e.g., compared to) the recovered Raman spectrum (and/ornormalized recovered Raman spectrum) to find a match.

By way of further non-limiting example, steps 710-770 can be applied(one or more times) to optical phantoms, each optical phantomhaving/mimicking a different concentration of a particular molecule ofmaterial 150 (FIG. 1). During calibration, the resulting recoveredspectrum from each phantom/concentration can be correlated with themolecule (and concentration) of that optical phantom. Using calibration,the correlation between the recovered Raman spectrum of the material andthe presence/concentration of a certain molecule can be established. Insome embodiments, the spectra generated during the calibration processare stored in a database and the actual Raman spectrum recovered whentaking real measurements can be compared to the stored spectra. Thecharacteristics of a matching stored spectrum can be associated with thematerial.

FIG. 8 is a graphical representation (e.g., plot, graph, and the like)800 of (relative) (received) light intensity or power in a.u. (arbitraryunits of intensity (other units can be milliwatts (mW) or photon count)along axis 210G over wavelength as wavenumber in cm⁻¹ (other units canbe nm) along axis 230E, according to some embodiments. For clarity,spectra 250F1 and 250F2 include fluorescence and systematic noise, anddo not include Raman scatter. For example, spectrum 250F₁ is from timewindow 330 (FIG. 3A) and spectrum 250F₁ has at least some of thecharacteristics of 250C₁. By way of further non-limiting example,spectrum 250F₂ is from time window 340 (FIG. 3A) and spectrum 250F₂ hasat least some of the characteristics of 250C₂. Spectrum 250F₃ is spectra250F₁ divided 250F₂. Accordingly, (in absence of Raman scatter) spectrum250F₃ is along axis 230E (is at a baseline, because there are no peaksfrom Raman scatter), which demonstrates that both fluorescence andsystematic noise are reduced by taking a ratio. In contrast, spectrum250F₄ is 250F₂ subtracted from spectra 250F₁, which results inmeaningless data. Spectrum 250F₄ demonstrates that not just anyarithmetic operation can be used to reduce fluorescence and/or systemicnoise. Moreover, other arithmetic operations cannot merely besubstituted for the arithmetic operations of the present technology.

FIG. 9 illustrates an exemplary computer system (or computing system)900 that may be used to implement some embodiments of the presentinvention. The computer system 900 in FIG. 9 may be implemented in thecontexts of the likes of computing systems, networks, servers, orcombinations thereof. The computer system 900 in FIG. 9 includesprocessor unit(s) 910 and main memory 920. Main memory 920 stores, inpart, instructions and data for execution by processor unit(s) 910. Mainmemory 920 stores the executable code when in operation, in thisexample. The computer system 900 in FIG. 9 further includes a mass datastorage 930, portable storage device 940, output devices 950, user inputdevices 960, a graphics display system 970, and peripheral device(s)980.

The components shown in FIG. 9 are depicted as being connected via asingle bus 990. The components may be connected through one or more datatransport means. Processor unit(s) 910 and main memory 920 are connectedvia a local microprocessor bus, and the mass data storage 930,peripheral device(s) 980, portable storage device 940, and graphicsdisplay system 970 are connected via one or more input/output (I/O)buses.

Mass data storage 930, which can be implemented with a magnetic diskdrive, solid state drive, or an optical disk drive, is a non-volatilestorage device for storing data and instructions for use by processorunit(s) 910. Mass data storage 930 stores the system software forimplementing embodiments of the present disclosure for purposes ofloading that software into main memory 920.

Portable storage device 940 operates in conjunction with a portablenon-volatile storage medium, such as a flash drive, floppy disk, compactdisk, digital video disc, or Universal Serial Bus (USB) storage device,to input and output data and code to and from the computer system 900 inFIG. 9. The system software for implementing embodiments of the presentdisclosure is stored on such a portable medium and input to the computersystem 900 via the portable storage device 940.

User input devices 960 can provide a portion of a user interface. Userinput devices 960 may include one or more microphones, an alphanumerickeypad, such as a keyboard, for inputting alphanumeric and otherinformation, or a pointing device, such as a mouse, a trackball, stylus,or cursor direction keys. User input devices 960 can also include atouchscreen. Additionally, the computer system 900 as shown in FIG. 9includes output devices 950. Suitable output devices 950 includespeakers, printers, network interfaces, and monitors.

Graphics display system 970 include a liquid crystal display (LCD) orother suitable display device. Graphics display system 970 isconfigurable to receive textual and graphical information and processesthe information for output to the display device.

Peripheral device(s) 980 may include any type of computer support deviceto add additional functionality to the computer system.

The components provided in the computer system 900 in FIG. 9 are thosetypically found in computer systems that may be suitable for use withembodiments of the present disclosure and are intended to represent abroad category of such computer components that are well known in theart. Thus, the computer system 900 in FIG. 9 can be a personal computer(PC), hand held computer system, telephone, mobile computer system,workstation, tablet, phablet, mobile phone, server, minicomputer,mainframe computer, wearable, or any other computer system. The computermay also include different bus configurations, networked platforms,multi-processor platforms, and the like. Various operating systems maybe used including UNIX, LINUX, WINDOWS, MAC OS, PALM OS, QNX, ANDROID,IOS, CHROME, and other suitable operating systems.

Some of the above-described functions may be composed of instructionsthat are stored on storage media (e.g., computer-readable medium). Theinstructions may be retrieved and executed by the processor. Someexamples of storage media are memory devices, tapes, disks, and thelike. The instructions are operational when executed by the processor todirect the processor to operate in accord with the technology. Thoseskilled in the art are familiar with instructions, processor(s), andstorage media.

In some embodiments, the computing system 900 may be implemented as acloud-based computing environment, such as a virtual machine and/orcontainer operating within a computing cloud. In other embodiments, thecomputing system 900 may itself include a cloud-based computingenvironment, where the functionalities of the computing system 900 areexecuted in a distributed fashion. Thus, the computing system 900, whenconfigured as a computing cloud, may include pluralities of computingdevices in various forms, as will be described in greater detail below.

In general, a cloud-based computing environment is a resource thattypically combines the computational power of a large grouping ofprocessors (such as within web servers) and/or that combines the storagecapacity of a large grouping of computer memories or storage devices.Systems that provide cloud-based resources may be utilized exclusivelyby their owners or such systems may be accessible to outside users whodeploy applications within the computing infrastructure to obtain thebenefit of large computational or storage resources.

The cloud is formed, for example, by a network of web servers thatcomprise a plurality of computing devices, such as the computing system600, with each server (or at least a plurality thereof) providingprocessor and/or storage resources. These servers manage workloadsprovided by multiple users (e.g., cloud resource customers or otherusers). Typically, each user places workload demands upon the cloud thatvary in real-time, sometimes dramatically. The nature and extent ofthese variations typically depends on the type of business associatedwith the user.

It is noteworthy that any hardware platform suitable for performing theprocessing described herein is suitable for use with the technology. Theterms “computer-readable storage medium” and “computer-readable storagemedia” as used herein refer to any medium or media that participate inproviding instructions to a CPU for execution. Such media can take manyforms, including, but not limited to, non-volatile media, volatile mediaand transmission media. Non-volatile media include, for example,optical, magnetic, and solid-state disks, such as a fixed disk. Volatilemedia include dynamic memory, such as system random-access memory (RAM).Transmission media include coaxial cables, copper wire and fiber optics,among others, including the wires that comprise one embodiment of a bus.Transmission media can also take the form of acoustic or light waves,such as those generated during radio frequency (RF) and infrared (IR)data communications. Common forms of computer-readable media include,for example, a floppy disk, a flexible disk, a hard disk, magnetic tape,any other magnetic medium, a CD-ROM disk, digital video disk (DVD), anyother optical medium, any other physical medium with patterns of marksor holes, a RAM, a programmable read-only memory (PROM), an erasableprogrammable read-only memory (EPROM), an electrically erasableprogrammable read-only memory (EEPROM), a Flash memory, any other memorychip or data exchange adapter, a carrier wave, or any other medium fromwhich a computer can read.

Various forms of computer-readable media may be involved in carrying oneor more sequences of one or more instructions to a CPU for execution. Abus carries the data to system RAM, from which a CPU retrieves andexecutes the instructions. The instructions received by system RAM canoptionally be stored on a fixed disk either before or after execution bya CPU.

Computer program code for carrying out operations for aspects of thepresent technology may be written in any combination of one or moreprogramming languages, including an object oriented programming languagesuch as JAVA, SMALLTALK, C++ or the like and conventional proceduralprogramming languages, such as the “C” programming language or similarprogramming languages. The program code may execute entirely on theuser's computer, partly on the user's computer, as a stand-alonesoftware package, partly on the user's computer and partly on a remotecomputer or entirely on the remote computer or server. In the latterscenario, the remote computer may be connected to the user's computerthrough any type of wired and/or wireless network, including a(wireless) local area network (LAN/WLAN) or a (wireless) wide areanetwork (WAN/WWAN), or the connection may be made to an externalcomputer (for example, through the Internet using an Internet ServiceProvider, wireless Internet provider, and the like).

The corresponding structures, materials, acts, and equivalents of allmeans or step plus function elements in the claims below are intended toinclude any structure, material, or act for performing the function incombination with other claimed elements as specifically claimed. Thedescription of the present technology has been presented for purposes ofillustration and description, but is not intended to be exhaustive orlimited to the invention in the form disclosed. Many modifications andvariations will be apparent to those of ordinary skill in the artwithout departing from the scope and spirit of the invention. Exemplaryembodiments were chosen and described in order to best explain theprinciples of the present technology and its practical application, andto enable others of ordinary skill in the art to understand theinvention for various embodiments with various modifications as aresuited to the particular use contemplated.

Aspects of the present technology are described above with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems) and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer program instructions. These computer program instructions maybe provided to a processor of a general purpose computer, specialpurpose computer, or other programmable data processing apparatus toproduce a machine, such that the instructions, which execute via theprocessor of the computer or other programmable data processingapparatus, create means for implementing the functions/acts specified inthe flowchart and/or block diagram block or blocks.

These computer program instructions may also be stored in a computerreadable medium that can direct a computer, other programmable dataprocessing apparatus, or other devices to function in a particularmanner, such that the instructions stored in the computer readablemedium produce an article of manufacture including instructions whichimplement the function/act specified in the flowchart and/or blockdiagram block or blocks.

The computer program instructions may also be loaded onto a computer,other programmable data processing apparatus, or other devices to causea series of operational steps to be performed on the computer, otherprogrammable apparatus or other devices to produce a computerimplemented process such that the instructions which execute on thecomputer or other programmable apparatus provide processes forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods and computer program products according to variousembodiments of the present technology. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof code, which comprises one or more executable instructions forimplementing the specified logical function(s). It should also be notedthat, in some alternative implementations, the functions noted in theblock may occur out of the order noted in the figures. For example, twoblocks shown in succession may, in fact, be executed substantiallyconcurrently, or the blocks may sometimes be executed in the reverseorder, depending upon the functionality involved. It will also be notedthat each block of the block diagrams and/or flowchart illustration, andcombinations of blocks in the block diagrams and/or flowchartillustration, can be implemented by special purpose hardware-basedsystems that perform the specified functions or acts, or combinations ofspecial purpose hardware and computer instructions.

The description of the present technology has been presented forpurposes of illustration and description, but is not intended to beexhaustive or limited to the invention in the form disclosed. Manymodifications and variations will be apparent to those of ordinary skillin the art without departing from the scope and spirit of the invention.Exemplary embodiments were chosen and described in order to best explainthe principles of the present technology and its practical application,and to enable others of ordinary skill in the art to understand theinvention for various embodiments with various modifications as aresuited to the particular use contemplated.

1. A method for reducing fluorescence and systemic noise in time-gatedspectroscopy, the method comprising: providing first light using anexcitation light source; receiving, by a detector, first scattered lightfrom a material responsive to the first light during a first time windowhaving a first duration, the first scattered light having substantialRaman signal, the first scattered light having a first wavelength;detecting a peak intensity of the first scattered light; receiving, bythe detector, second scattered light from the material responsive to thefirst light during a second time window having a second duration, thesecond scattered light having little Raman signal, the second scatteredlight having the first wavelength; detecting a peak intensity of thesecond scattered light; providing second light using the excitationlight source; receiving, by the detector, third scattered light from thematerial responsive to the second light during a third time windowhaving the first duration, the third scattered light having substantialRaman signal, the third scattered light having a second wavelength;detecting a peak intensity of the third scattered light; receiving, bythe detector, fourth scattered light from the material responsive to thesecond light during a fourth time window having the second duration, thefourth scattered light having little Raman signal, the fourth scatteredlight having the second wavelength; detecting a peak intensity of thefourth scattered light; recovering a spectrum of the material; andidentifying at least one molecule of the material.
 2. The method ofclaim 1 further comprising: providing third light using the excitationlight source; receiving, by the detector, fifth scattered light from thematerial responsive to the third light during a fifth time window havingthe first duration, the fifth scattered light having substantial Ramansignal, the fifth scattered light having a third wavelength; detecting apeak intensity of the fifth scattered light; receiving, by the detector,sixth scattered light from the material responsive to the third lightduring a sixth time window having the second duration, the sixthscattered light having little Raman signal, the sixth scattered lighthaving the third wavelength; and detecting a peak intensity of the sixthscattered light; wherein the recovering the spectrum of the materialfurther includes taking a ratio of the peak intensity of the fifthscattered light and the peak intensity of the sixth scattered light. 3.The method of claim 1, further comprising: normalizing the recoveredspectrum to produce a normalized recovered spectrum; and identifying atleast one molecule of the material using the normalized recoveredspectrum and a database of identified spectra.
 4. The method of claim 3,wherein normalizing the recovered spectrum includes: fitting therecovered spectrum to a baseline using at least one of linear regressionand polynomial curve fitting; and subtracting the baseline from therecovered spectrum to produce the normalized recovered spectrum.
 5. Themethod of claim 1, wherein the substantial Raman signal is 80%-100% ofpeak intensity of a respective Raman signal.
 6. The method of claim 5,wherein the little Raman signal is 0%-20% of peak intensity of therespective Raman signal.
 7. The method of claim 1, wherein: the firstduration is shorter than the second duration; the second time windowbegins after the first time window ends; and the fourth time windowbegins after the third time window ends.
 8. The method of claim 19,wherein the detector is at least one of a single-photon avalanche diode(SPAD), micro-channel plate (MCP), photomultiplier tube (PMT), siliconphotomultiplier (SiPM), and avalanche photodiode (APD), and the detectoris disposed on at least one of a scanning motor driven rail, SPAD array,and an intensified CCD (ICCD).
 9. The method of claim 1, wherein thesystemic noise arises from spectrometer components producing multiplereflections that interfere with each other to generate an interferencepattern.
 10. The method of claim 1, wherein the material has a strongfluorescence background.
 11. A system for reducing fluorescence andsystemic noise in time-gated spectroscopy, the system comprising: aprocessor; and a memory, the memory communicatively coupled to theprocessor and storing instructions executable by the processor toperform a method, the method comprising: providing first light using anexcitation light source; receiving, by a detector, first scattered lightfrom a material responsive to the first light during a first time windowhaving a first duration, the first scattered light having substantialRaman signal, the first scattered light having a first wavelength;detecting a peak intensity of the first scattered light; receiving, bythe detector, second scattered light from the material responsive to thefirst light during a second time window having a second duration, thesecond scattered light having little Raman signal, the second scatteredlight having the first wavelength; detecting a peak intensity of thesecond scattered light; providing second light using the excitationlight source; receiving, by the detector, third scattered light from thematerial responsive to the second light during a third time windowhaving the first duration, the third scattered light having substantialRaman signal, the third scattered light having a second wavelength;detecting a peak intensity of the third scattered light; receiving, bythe detector, fourth scattered light from the material responsive to thesecond light during a fourth time window having the second duration, thefourth scattered light having little Raman signal, the fourth scatteredlight having the second wavelength; detecting a peak intensity of thefourth scattered light; recovering a spectrum of the material; andidentifying at least one molecule of the material.
 12. The system ofclaim 11, wherein the method further comprises: providing third lightusing the excitation light source; receiving, by the detector, fifthscattered light from the material responsive to the third light during afifth time window having the first duration, the fifth scattered lighthaving substantial Raman signal, the fifth scattered light having athird wavelength; detecting a peak intensity of the fifth scatteredlight; receiving, by the detector, sixth scattered light from thematerial responsive to the third light during a sixth time window havingthe second duration, the sixth scattered light having little Ramansignal, the sixth scattered light having the third wavelength; anddetecting a peak intensity of the sixth scattered light; wherein therecovering the spectrum of the material further includes taking a ratioof the peak intensity of the fifth scattered light and the peakintensity of the sixth scattered light.
 13. The system of claim 11,wherein the method further comprises: normalizing the recovered spectrumto produce a normalized recovered spectrum; and identifying at least onemolecule of the material using the normalized recovered spectrum and adatabase of identified spectra.
 14. The system of claim 13, whereinnormalizing the recovered spectrum includes: fitting the recoveredspectrum to a baseline using at least one of linear regression andpolynomial curve fitting; and subtracting the baseline from therecovered spectrum to produce the normalized recovered spectrum.
 15. Thesystem of claim 11, wherein the substantial Raman signal is 80%-100% ofpeak intensity of a respective Raman signal.
 16. The system of claim 15,wherein the little Raman signal is 0%-20% of peak intensity of therespective Raman signal.
 17. The system of claim 11, wherein: the firstduration is shorter than the second duration; the second time windowbegins after the first time window ends; and the fourth time windowbegins after the third time window ends.
 18. The system of claim 11,wherein the detector is at least one of a single-photon avalanche diode(SPAD), micro-channel plate (MCP), photomultiplier tube (PMT), siliconphotomultiplier (SiPM), and avalanche photodiode (APD), and the detectoris disposed on at least one of a scanning motor driven rail, SPAD array,and an intensified CCD (ICCD).
 19. The system of claim 11, wherein thesystemic noise arises from spectrometer components producing multiplereflections that interfere with each other to generate an interferencepattern.
 20. A system for reducing fluorescence and systemic noise intime-gated spectroscopy, the system comprising: means for providingfirst light using an excitation light source; receiving, by a detector,first scattered light from a material responsive to the first lightduring a first time window having a first duration, the first scatteredlight having substantial Raman signal, the first scattered light havinga first wavelength; means for detecting a peak intensity of the firstscattered light; means for receiving, by the detector, second scatteredlight from the material responsive to the first light during a secondtime window having a second duration, the second scattered light havinglittle Raman signal, the second scattered light having the firstwavelength; means for detecting a peak intensity of the second scatteredlight; means for providing second light using the excitation lightsource; means for receiving, by the detector, third scattered light fromthe material responsive to the second light during a third time windowhaving the first duration, the third scattered light having substantialRaman signal, the third scattered light having a second wavelength;means for detecting a peak intensity of the third scattered light; meansfor receiving, by the detector, fourth scattered light from the materialresponsive to the second light during a fourth time window having thesecond duration, the fourth scattered light having little Raman signal,the fourth scattered light having the second wavelength; means fordetecting a peak intensity of the fourth scattered light; means forrecovering a spectrum of the material; and means for identifying atleast one molecule of the material.